Despite advances in medicine and technology, clinical outcomes among patients diagnosed with stage 5 chronic kidney disease (CKD) on maintenance hemodialysis (MHD) have remained suboptimal. In the United States, one out of two patients receiving maintenance dialysis will die within three years of initiating renal replacement therapy. This is an important problem, given the over one-half million individuals in the US who are affected, the high cost in human suffering and loss, and the expense to Medicare and private insurance. Causes for this population's high mortality rate are multifactorial and interdependent. Protein-energy malnutrition or wasting has emerged as an independent risk factor for mortality in this population. The decline in kidney function leads to a spontaneous reduction in appetite and oral intake, coupled with physiological alterations in nutrient and energy metabolism. To offset the consequent sequelae of the disease process, nutritional care must be optimized. Effective nutritional intervention requires an appropriate predictive energy equation, based on an understanding of clinical factors, mechanisms, and an accurate determination of energy expenditure (EE). Currently no such understanding or equation exists for this patient population. Therefore, this proposed study seeks to characterize the relevant parameters, contribute to the understanding of this significant clinical condition, an generate a predictive energy equation specifically for use in patients with advanced CKD, thereby improving clinical practice and reducing patient morbidity and mortality. The goals of our proposed study are 1) to determine what clinical factors predict EE in patients diagnosed with stage 5 CKD on MHD; 2) to develop and validate a predictive energy equation that incorporates all of the influencing clinical factors measured in stage 5 CKD patients on MHD; and 3) to further test the clinical utility and application of this equation. We will accomplish these aims using a 2 year, multi-site, cross-sectional study with a split-sample design that affords numerous opportunities for undergraduate and graduate students to participate in the research process. The proposed study will use multiple sites to assure appropriate demographic and clinical representation and content expertise in all aspects of the project. Consistent with our power estimations, each research site plans to enroll 75 participants of diverse races and ethnicities, representative of the geographic regions and the larger population of MHD patients. It is anticipated that enrollment will occur in a two-phase process: 1) development of the predictive energy equation (Phase 1) and 2) validation of the equation (Phase 2). Once enrolled, the participants will have their resting EE and body composition measured as well as key laboratory parameters collected (e.g., iPTH, CRP, A1C) in order to determine what, if any, factors impact EE. PUBLIC HEALTH RELEVANCE: Partly responsible for the poor outcomes in patients diagnosed with kidney disease on dialysis is the malnourished condition often experienced by these individuals. Quality nutrition care for dialysis patients can only be provided when practitioners have appropriate methods to evaluate the metabolic rate accurately. This proposed study will plan to develop a formula that will precisely determine the number of calories a dialysis patient requires in order to thwart further compromise in health condition.